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PRACTITIONER APPLICATION: Can Inbound and Domestic Medical Tourism Improve Your Bottom Line? Identifying the Potential of a U.S. Tourism Market

2014· article· en· W2773295168 on OpenAlexaboutno aff
Steven C. Foster

Bibliographic record

VenueJournal of Healthcare Management · 2014
Typearticle
Languageen
FieldHealth Professions
TopicGlobal Healthcare and Medical Tourism
Canadian institutionsnot available
Fundersnot available
KeywordsRevenueBusinessHealth carePrivilege (computing)Medical tourismTourismReimbursementPopulationMarketingSuspectCompetitor analysisPublic relationsEconomic growthMedicineFinancePolitical scienceEconomicsLaw

Abstract

fetched live from OpenAlex

There is little argument that the healthcare industry continues to change at a fast rate. In fact, many healthcare organizations have had to evolve—if not reinvent themselves—to keep up with industry changes or risk being left in the wake of their competitors. At present, I see no sign of slowed momentum with healthcare reform. This means that today's healthcare administrator must become comfortable navigating unfamiliar waters and be willing to look at new sources of revenue to overcome a landscape characterized by reduced reimbursement. Fottler et al. present a market perspective that has received limited research attention. Yet, I suspect that many domestic hospitals realize the potential of attracting the medical tourist segment and have, at one point or another, created strategic initiatives to support both inbound and domestic medical tourism. As a practitioner, I have had the privilege of experiencing all forms of medical tourism described in this article, including helping to grow a successful international center for inbound medical patients in a world-class academic medical center, managing hospitals in foreign countries that provide less costly care for American patients unable or unwilling to pay for their domestic insurance copays, and overseeing a hospital in the southern United States that serves the snowbird population from Canada and the northern U.S. states. On the basis of my experience, I concur with Fottler et al.'s conclusion that these markets represent potentially significant revenue streams. In this study, the authors looked at a comprehensive data set to determine the utilization of healthcare services for a large urban healthcare system. While it is true that geographical, environmental, and individual facility (e.g., brand, reputation) factors attract medical tourists to healthcare organizations, all administrators should study their hospital admissions to determine origination patterns. Understanding current patient demographics and reviewing information from local convention and visitors bureaus may help organizations discover an untapped market for their hospital. In addition to the external marketing plan the authors describe, organizations should review internal programs to determine if changes are warranted in areas such as translation services that cover patient education. Nutritional needs and diets may also require review to ensure alignment with the patient's country of origin. Finally, hospital staff may require culture-specific training to understand patients' traditions and customs. In summary, healthcare administrators should recognize the potential that inbound and domestic medical tourism offers. While understanding why medical tourists visit certain hospitals is important, knowing the key satisfiers that grow future volume is essential. Experience suggests that facilities that formalize strategies with specific goals and established resources for inbound and domestic medical tourism outperform those facilities with unorganized approaches for this market.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.006
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.848
Threshold uncertainty score0.845

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0060.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.002
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.026
GPT teacher head0.398
Teacher spread0.371 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations2
Published2014
Admission routes1
Has abstractyes

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